In this paper we consider nonparametric estimation in panel data under cross sectional dependence. Both the number of cross sectional units (N) and the time dimension of the panel (T) are assumed to be large, and the cross sectional dependence has a multifactor structure. Local linear regression is used to filter the unobserved cross sectional factors and to estimate the nonparametric conditional mean. A Monte Carlo study shows that the proposed estimator yields satisfactory finite sample properties.